Abstract: The described implementations relate to patient identification. One implementation can acquire binary biometric data and structured data from a patient. This implementation can compare the acquired patient binary biometric data and structured data to binary biometric data and structured data associated with patient files in an electronic master patient index.

Abstract: The described implementations relate to expressing terminologies in a hierarchical form. One implementation can receive a terminology that can include concept-code pairs. For example, each of the concept-code pairs can include a concept and a code that is assigned to the concept by the terminology. The implementation can map the concepts to levels of a hierarchical ontology, and associate some of the concepts across different levels of the hierarchical ontology. The implementation can also provide programmatic access to the concept-code pairs of the terminology via the hierarchical ontology.

Abstract: One or more techniques and/or systems are disclosed that provide for document retrieval where a user can identify key attributes of potential target documents that are desirable (e.g., have a particular semantic content for the user). Further, relevant documents that comprise the desired semantic content can be retrieved. Additionally, the user can provide feedback on the retrieved documents, for example, based on key semantic concepts found in the documents, and the input can be used to update the classification. For example, this process can be iterated to improve the retrieval and precision of documents found through machine learning techniques.

Abstract: The described implementations relate to patient identification. One implementation can acquire binary biometric data and structured data from a patient. This implementation can compare the acquired patient binary biometric data and structured data to binary biometric data and structured data associated with patient files in an electronic master patient index.

Abstract: A de-identification system is described herein for converting original messages into de-identified messages. The de-identification system leverages original message-inception-functionality which operates as a gateway for providing original messages for use by a production environment. Namely, the de-identification system includes a transformation module that receives the original messages from the original message-inception functionality. The transformation module then converts instances of sensitive information contained in the original messages into non-sensitive information, to produce the de-identified messages. A de-identified environment can consume the de-identified messages with high confidence that the messages have been properly sanitized. This is because the de-identification work has been performed at a well-contained quarantine level of the message processing functionality.

Abstract: One or more techniques and/or systems are disclosed that provide for document retrieval where a user can identify key attributes of potential target documents that are desirable (e.g., have a particular semantic content for the user). Further, relevant documents that comprise the desired semantic content can be retrieved. Additionally, the user can provide feedback on the retrieved documents, for example, based on key semantic concepts found in the documents, and the input can be used to update the classification. For example, this process can be iterated to improve the retrieval and precision of documents found through machine learning techniques.